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Found 6 papers, 3 papers with code
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning
Multi-agent reinforcement learning has recently shown great promise as an approach to networked system control.
Causal Multi-Agent Reinforcement Learning: Review and Open Problems
This paper serves to introduce the reader to the field of multi-agent reinforcement learning (MARL) and its intersection with methods from the study of causality.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Brain Structural Saliency Over The Ages
Brain Age (BA) estimation via Deep Learning has become a strong and reliable bio-marker for brain health, but the black-box nature of Neural Networks does not easily allow insight into the features of brain ageing. We trained a ResNet model as a BA regressor on T1 structural MRI volumes from a small cross-sectional cohort of 524 individuals.
Off-the-Grid MARL: Datasets with Baselines for Offline Multi-Agent Reinforcement Learning
However, offline MARL is still in its infancy and therefore lacks standardised benchmark datasets and baselines typically found in more mature subfields of reinforcement learning (RL).
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Reduce, Reuse, Recycle: Selective Reincarnation in Multi-Agent Reinforcement Learning
'Reincarnation' in reinforcement learning has been proposed as a formalisation of reusing prior computation from past experiments when training an agent in an environment.
A Sequence Modelling Approach to Question Answering in Text-Based Games
Interactive Question Answering (IQA) requires an intelligent agent to interact with a dynamic environment in order to gather information necessary to answer a question.
